Hossein Shahi
Papers
2
Total Citations
8
H-Index
2
About
Hossein Shahi is a robotics researcher specializing in the control of exoskeleton systems, with a focus on enhancing human-robot interaction in rehabilitation and augmentation applications. His work addresses one of the most challenging issues in the field: managing the structured and unstructured uncertainties inherent in exoskeleton dynamics. In his most cited paper (2018, 6 citations), Shahi introduced a robust adaptive admittance control scheme that combines a composite adaptive feedback law with a Locally Weighted Projection Regression (LWPR) estimator. This approach enables the exoskeleton to estimate and compensate for uncertainties in real time, allowing for more natural and stable user-in-charge operation. His earlier work (2015, 2 citations) further explored impedance control performance improvements under uncertain conditions, laying the groundwork for more reliable and responsive exoskeleton suits. While his citation counts are modest, Shahi’s contributions are technically significant, offering practical solutions to the complex control problems that limit the real-world deployment of wearable robotic systems. His research is particularly valuable for students and engineers working on adaptive control, human-robot interaction, and rehabilitation robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2